2 citations · 2 across the 8 of their papers we have counts for
12 papers · 1 filter
SciRisk-Bench: A Risk-Dimension-Aware Benchmark for AI4Science Safety
Linghao Feng, Yinqian Sun, Dongqi Liang +8
Large language models (LLMs) are increasingly embedded in AI for Science (AI4Science) workflows, from scientific question answering and literature analysis to laboratory planning a…
ForesightSafety-SAGE:A Fully Automated Scenario Generation and Safety Evaluation Framework for LLM Agents
Lu Jia, Haibo Tong, Feifei Zhao +5
Large language models (LLMs) are increasingly evolving from simple text-based interaction systems into LLM agents that can maintain memory, use tools, access external environments,…
CogManip: Benchmarking Manipulative Behavior in Multi-Turn Interactions with Large Language Model
Zeyang Yue, Chenfei Yan, Feifei Zhao +5
Whether Large Language Models (LLMs) exhibit covert psychological manipulation in complex human-AI interactions has garnered increasing safety concerns. However, existing AI safety…
ForesightSafety Bench: A Frontier Risk Evaluation and Governance Framework towards Safe AI
Haibo Tong, Feifei Zhao, Linghao Feng +18
Rapidly evolving AI exhibits increasingly strong autonomy and goal-directed capabilities, accompanied by derivative systemic risks that are more unpredictable, difficult to control…
Light Alignment Improves LLM Safety via Model Self-Reflection with a Single Neuron
Sicheng Shen, Mingyang Lv, Han Shen +7
The safety of large language models (LLMs) has increasingly emerged as a fundamental aspect of their development. Existing safety alignment for LLMs is predominantly achieved throu…
CogToM: A Comprehensive Theory of Mind Benchmark inspired by Human Cognition for Large Language Models
Haibo Tong, Zeyang Yue, Feifei Zhao +6
Whether Large Language Models (LLMs) truly possess human-like Theory of Mind (ToM) capabilities has garnered increasing attention. However, existing benchmarks remain largely restr…